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TRNA^Arg-Derived Fragments Can Serve as Arginine Donors for Protein Arginylation.

ABSTRACT: Arginyltransferase ATE1 mediates posttranslational arginylation and plays key roles in multiple physiological processes. ATE1 utilizes arginyl (Arg)-tRNA^Arg as the donor of Arg, putting this reaction into a direct competition with the protein synthesis machinery. Here, we address the question of ATE1- Arg-tRNA^Arg specificity as a potential mechanism enabling this competition in vivo. Using in vitro arginylation assays and Ate1 knockout models, we find that, in addition to full-length tRNA, ATE1 is also able to utilize short tRNA^Arg fragments that bear structural resemblance to tRNA-derived fragments (tRF), a recently discovered class of small regulatory non-coding RNAs with global emerging biological role. Ate1 knockout cells show a decrease in tRF^Arg generation and a significant increase in the ratio of tRNA^Arg:tRF^Arg compared with wild type, suggesting a functional link between tRF^Arg and arginylation. We propose that generation of physiologically important tRFs can serve as a switch between translation and protein arginylation.

SUBMITTER: Avcilar-Kucukgoze I

PROVIDER: S-EPMC7409373 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundtRNA-derived fragments (tRFs) are 14-40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes.MethodsWe used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models.ResultsWe first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977-0.983) in the training process and an AUC = 0.847 (0.83-0.861) in the test process. The model was applied to all the sites with perfect Watson-Crick complementarity to the seed in the 3' untranslated region (3'-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. We also validated the predictions via quantitative real-time PCR (qRT-PCR). Thirteen potential target genes from the top of the predictions were significantly down-regulated at the mRNA levels by overexpression of the tRFs (tRF-3001a, tRF-3003a or tRF-3009a).ConclusionsPredictions can be obtained online, tRFTars, freely available at http://trftars.cmuzhenninglab.org:3838/tar/ , which is the first tool to predict targets of tRFs in humans with a user-friendly interface.

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TRNAArg-Derived Fragments Can Serve as Arginine Donors for Protein Arginylation.

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TRNA^Arg-Derived Fragments Can Serve as Arginine Donors for Protein Arginylation.